Real-time prediction for an EV Battery Thermal Management

Leveraging closed control loop with real-time prediction using nvision, an AI-powered surrogate modelling tool by Noesis Solutions

First name*

Last name*

Company*

E-mail*

Phone number

Country

I consent to the Noesis Solutions Privacy Notice and the Terms of Use of this website.

I understand my personal data will be processed with regard to my request to receive this copy and newsletter and in accordance with the Privacy Policy.

Revolutionize EV Battery Thermal Management with AI

Efficient thermal management is crucial for maintaining the performance, safety, and longevity of electric vehicle (EV) batteries. Traditional methods rely on time-consuming analytical calculations that struggle to account for dynamic factors like State-of-Charge (SOC) and ambient temperature. This case study reveals how cloud-based simulations by SimScale and AI-powered surrogate models by nvision can transform EV battery performance prediction.

In this case study, we explore:

How SimScale’s cloud-native simulations create high-fidelity thermal response data
How nvision’s AI-based surrogate models reduce simulation time from 1 hour to under 1 minute
How real-time predictions optimize coolant power, enhancing battery lifespan and efficiency
How this approach enables scalable, dynamic, and sustainable EV battery solutions

Download the case study to know more…

Download your copy »

©2025 Noesis Solutions • Use of this website is subject to our legal disclaimer
Cookie policy • Cookie Settings • Privacy Notice • Design & Development by Zenjoy